Federal emissions regulations mandate the reformulation of fuels, such as gasoline fuel, sold at pumps to reduce the content of toxic and ozone-forming compounds in vehicle emissions. For example, to reduce the emission of volatile organic compounds (VOC), fuels sold in southern areas (e.g., areas categorized under ASTM class B) may be required to have a lower Reid vapor pressure (RVP) as compared to fuels sold in northern areas (e.g., areas categorized under ASTM class C) during summer months. Specifically, the differences in climate between the two types of areas may require a corresponding difference in the gasoline fuel volatility to achieve the same emissions effect. Therefore, depending on the seasonal temperatures and geographic locations, commercial fuel distributors may vary the composition of a given fuel. As a result, based on when and where a fuel tank (FT) was refilled with a given fuel, the fuel volatility and the RVP of the fuel may differ.
Fuel volatility has a direct consequence on the efficiency of an internal combustion engine (ICE). For example, combustion air-fuel ratio, which is a factor in determining fuel injection to an engine cylinder, is affected by fuel volatility. On-board diagnostic monitors of an engine control also apply fuel volatility estimates, for example in the monitoring and detection of fuel system leaks. One example approach for fuel volatility detection is shown by Grant et al. in US 2009/0114288 A1. Therein, based on the ideal gas law, and further based on fuel tank pressure and temperature sensor measurements, a controller determines the volatility of a fuel filled into the fuel tank. In other approaches, fuel volatility may be inferred from a fuel alcohol content, as estimated based on the output of an exhaust gas oxygen sensor. Still other approaches may use engine speed and torque data to infer fuel volatility.
However, the inventors herein have identified potential issues with such approaches. As one example, some of the above approaches rely on engine operation and cylinder combustion to be able to detect and estimate fuel volatility. In hybrid vehicles, where combustion may not occur for extended periods of time, an accurate and current fuel volatility estimate may not be available when needed. As another example, approaches relying on fuel tank pressure and temperature data may generate incorrect results due to fuel tank temperature acting as a control factor, as well as a noise factor. For example, depending on how long a vehicle engine was on before the temperature and pressure data was collected may affect how much heat was rejected from the running engine to the fuel tank. Likewise, a temperature of the parking surface where the vehicle is parked, as well as wind and sun loading on the fuel system, may cause the fuel tank temperature and pressures to fluctuate, resulting in variations in fuel volatility estimates. Incorrect fuel volatility estimates may in turn corrupt leak test results. For example, a fuel that is actually more volatile than estimated may offset a true leak and trigger a false positive in an engine-off natural vacuum (EONV) leak test. As another example, a fuel that is actually more volatile than estimated may overwhelm a vacuum pump and trigger a false negative when used in a vacuum pump assisted leak test. In either case, the false result can lead to a leak not being correctly identified and degraded exhaust emissions.
In one example, the above issues may be addressed, at least in part, by a method for accurately estimating fuel volatility in a hybrid vehicle system. One example method for an engine, comprises: adjusting a leak test based on a fuel volatility, the fuel volatility estimated during a vehicle-off condition after a refueling event. In this way, fuel volatility determination can be performed in hybrid vehicles during a vehicle-off condition without dependence on engine activity.
For example, during a vehicle-off condition following a refueling event, the controller (e.g., a powertrain control module or PCM) of a hybrid vehicle system may be woken up after a long duration in sleep mode (e.g., in hours). The duration may be long enough to allow the temperature and pressure in the fuel tank to stabilize. Upon waking up, the controller may monitor changes in fuel tank pressure and temperature over a short duration of time (e.g., in minutes or seconds). If changes in fuel tank pressure and temperature are not greater than a threshold change (that is, fuel tank conditions remain stable), fuel volatility estimation conditions may be considered met. Accordingly, the fuel tank may be sealed and a fuel pump may be activated (without operating the engine) to agitate fuel in the tank, leading to an increase in fuel tank pressure. A peak pressure achieved at the given fuel temperature may be used to estimate fuel RVP. For example, the estimated peak pressure value may be compared to predetermined data for known fuel RVPs stored in a look-up table of the controller and used to update a fuel volatility estimate of refilled fuel.
The fuel volatility estimate can then be utilized to adjust engine operating parameters, such as a leak test threshold for evaporative emission leak detection tests. For example, when leak test conditions are met, a positive or negative pressure may be applied to the isolated fuel tank until a threshold pressure level is reached. Then, a rate of change of pressure (to barometric pressure) may be monitored. A fuel system leak may be indicated if the rate of change of pressure is greater than the leak test threshold (wherein the threshold was based on the estimated fuel volatility).
In this way, fuel volatility may be estimated in a hybrid vehicle having limited engine run times. By estimating fuel volatility during selected vehicle-off conditions by operating a fuel pump, fuel volatility may be determined without relying on engine combustion. By adjusting engine operating parameters, such as a leak test threshold, based on an updated fuel volatility estimate, more robust and accurate leak diagnostic results are achieved. By improving the accuracy of leak detection, exhaust emissions may be improved.
It should be understood that the summary above is provided to introduce in simplified form a selection of concepts that are further described in the detailed description. It is not meant to identify key or essential features of the claimed subject matter, the scope of which is defined uniquely by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to implementations that solve any disadvantages noted above or in any part of this disclosure.